Sparse Generative Adversarial Network

20 Aug 2019Shahin MahdizadehaghdamAshkan PanahiHamid Krim

We propose a new approach to Generative Adversarial Networks (GANs) to achieve an improved performance with additional robustness to its so-called and well recognized mode collapse. We first proceed by mapping the desired data onto a frame-based space for a sparse representation to lift any limitation of small support features prior to learning the structure... (read more)

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